lisan-Hopfield-Shenjingwangluo

有一学生成绩管理数据库如下表，要求建立一SAS数据集score，并输出显示 创建一个新的数据集class，新增平均成绩aver变量和等级考评grade变量，grade的值是根据aver值的大小给出A、B、C、D四个等级，并显示新数据集class(A student achievement management database as the table, called for the establishment of a SAS data set score, and output display create a new data set class, add an average score aver evaluation variables and grade level variables, grade values are based on the size of a aver value the A, B, C, D four grades, and displays the new data set of class)

matlab编写的电压稳定分析程序，电力专业必备(matlab prepared procedures for voltage stability analysis, power professional must)

多帧图像超分辨率重建，里面有huber 马尔科夫，ML超分辨率重建，对学习超分辨率很有帮助。(Multi-frame image super-resolution reconstruction, which has the the huber Markov, ML super-resolution reconstruction is helpful in learning the super-resolution.)

一种基于Boost电路的光伏最大功率跟踪方法,内部详细介绍了BOOST电路的原理及其在光伏发电中实现MPPT跟踪，值得学习。(Boost circuit-based photovoltaic maximum power point tracking method, the internal details of the BOOST circuit theory and its application in photovoltaic MPPT tracking is implemented, it is worth learning.)

DBT, A Matlab and Octave toolbox for radar modelling, signal simulation and processing. Release 2.156

说明：  快速迭代收缩阈值算法，FISTA用一种更为聪明的办法选择序列{xk}，使得其基于梯度下降思想的迭代过程更加快速地趋近问题函数F(x)的最小值。FISTA的缺点是：Lipschitz常数L(f)不一定可知或者可计算。(Fast iterative contraction threshold algorithm, FISTA uses a more clever method to select the sequence{xk}, making its iterative process based on the gradient descent idea more quickly approach the minimum value of the problem function F(X). The disadvantage of FISTA is that the Lipschitz constant L(f) is not necessarily known or computable.)

数值分析算法matlab：清华大学出版社数值分析课后实验计算题9个matlab程序和实验报告(Numerical_Analysis_of_algorithms matlab)

用LMS算法实现自适应均衡器的MATLAB程序(LMS)

some use full matlab code for student who start learning Powerflow-analysis by matlab , it contain - PDF tutorial for starter - .m solution file for tutorial assignment -.m powerflow analysis program using newton-rapson method

《MATLAB高效编程技巧与应用：25个案例分析》源程序 数据(The "MATLAB efficient programming techniques and applications: 25 Case Studies" code and data)